The London-based quantum technology startup will use the funds to grow its software platform, which is designed for the life sciences and materials science sectors.

QMatter, a London-based quantum technology startup, has raised $1.2 million (£890,000) in a pre-seed funding round to accelerate the development of its quantum compression platform designed for the life sciences and materials science sectors.

The round was led by quantum fund 55 North with additional participation from XTX Ventures, Bellstate Oy, and the Conception X Angel Syndicate. The company will use the capital to grow its software platform, which aims to overcome the hardware limitations currently preventing quantum computers from solving industrially relevant problems.

Simulating quantum mechanics is a critical requirement for breakthrough discoveries in drug development and materials design, yet the process remains extremely computationally demanding. Current hardware, both classical and quantum, often lacks the capacity to handle the most complex challenges. Today’s quantum systems specifically suffer from limited qubit counts and instability, which keep the most commercially valuable simulations out of reach.

QMatter’s compression technology applies principles from quantum mechanics to reduce the size of a problem before it is processed. This approach is designed to extend the capabilities of near-term and future quantum computers while simultaneously accelerating classical algorithms on everything from consumer hardware to large-scale supercomputers.

The company is currently focused on the life sciences market, collaborating with pharmaceutical and biotechnology firms to improve research outcomes through more accurate simulation data. Parallel to its software development, QMatter is generating physics-informed data libraries, which provide a new resource for machine learning companies to train next-generation AI models using problem-specific data that was previously unavailable.

“QMatter compresses complex quantum problems to their essential core, ensuring solutions remain both accurate and useful,” said co-founder and chief executive Alexis Ralli.

“By doing so, we unlock greater performance from today’s quantum hardware while broadening the problem landscape for future error-corrected machines.”